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Image Provenance

All articles tagged with #image provenance

technology24 days ago•4 min saved

Apple unveils Reference Image: a quantum-secure, verifiable photo provenance system

Apple’s Security Research blog details Reference Image, a new iPhone 18 Pro camera mode that creates a verifiable, privacy-preserving photo provenance chain. The system signs raw sensor data with a device-specific key, uses cryptographic timestamps, and runs through Private Cloud Compute to produce a secure digital negative that can be revoked if later found fraudulent. It begins at manufacturing with a factory-signed key, uses post-quantum signing, and aims to keep photographer identity private while ensuring authenticity even against future quantum threats and potential edits.

via 9to5Mac|

#apple #image-provenance #photography

technology25 days ago•8 min saved

Apple Rolls Out Cryptographically Verified Photos With Reference Image

Apple's iPhone 18 Pro introduces Apple Reference Image, a secure mode that signs raw pixel data immediately after capture to create a cryptographic 'digital negative' stored on-device; when verification is requested, the negative is processed in Private Cloud Compute to render a tamper-evident image in a secure environment. The system aims to prove photos were taken by a real iPhone sensor at a specific time, resists various attacks, is quantum-secure, opt-in, and limited to the main camera sensor, with revocation if fraud is detected.

via MacRumors|

#apple #image-provenance #photography

science3 months ago•12 min saved

When AI fabricates science: trust hinges on image provenance

AI-made scientific images can look convincingly real, challenging journals and the public to tell them apart and risking a broader crisis of trust in science. High-profile cases—AI-generated figures in 2024 papers and an AI-modified image triggering a 2026 NEJM retraction—show how detectors can lag behind image creation. As visual credibility has long rested on provenance, institutional authority, and alignment with observed data, generative AI erodes those cues. The path forward is transparency: clear disclosure of image provenance (AI-generated or not), explicit explanations of what the image represents, verification and reproducibility details, and cross-field standards for image integrity. Ultimately, public trust depends on documenting the link between visuals and verifiable scientific reality, not on sleek visuals alone.

via The Conversation|

#ai #ai-generated-images #image-provenance